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3rd IFAC Workshop on Navigation, Guidance and control of Underwater Vehicles, NGCUV 2012

作者： Soares, Jorge M. Aguiar, A. Pedro Pascoal, António M. Gallieri, Marco Laboratory of Robotics and Systems in Engineering and Science Instituto Superior Técnico Technical University of Lisbon Av. Rovisco Pais 1049-001 Lisboa Portugal CH-1015 Lausanne Switzerland Control Group Engineering Department Sidney Sussex College CB21PZ Cambridge United Kingdom

ISBN: (纸本)9783902823199

This paper addresses the problem of maintaining an autonomous robotic vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The robotic vehicle has no a priori knowledge of the path described by the leaders and its goal is to follow them by constantly regulating the inter-vehicle distances to a desired fixed value, using range-only measurements. To solve this station keeping problem, we propose a control strategy that estimates the formation speed and heading from the ranges obtained to the two leading vehicles, and uses simple feedback laws for speed and heading commands to drive suitably defined common and differential errors to zero. For straight-line motion, we provide guaranteed conditions under which the proposed control strategy achieves local convergence of the distance errors to zero. We also indicate how our design procedure can be extended to full dynamic models of marine robotic vehicles equipped with inner loops for yaw and speed control. Simulation results using realistic models are described and discussed.

关键词： Vehicles

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Surface sensor networks for Underwater Vehicle positioning with bearings-only measurements

Surface sensor networks for Underwater Vehicle positioning w...

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2012 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： D. Moreno-Salinas A. M. Pascoal J. Aranda Department of Computer Science and Automatic Control UNED Madrid Spain Laboratory of Robotics and Systems in Engineering and Science (LARSyS) Technical University of Lisbon Portugal

There is increasing interest in the use of Autonomous Underwater Vehicles (AUVs) to substantially improve the means available for ocean exploration and exploitation. A key element in the operation of certain classes of AUVs is the availability of good underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or a set of autonomous surface vehicles. In an interesting operational scenario, the set of autonomous surface vehicles carries a network of acoustic units that measure the elevation and azimuth angles between the target and each of the receivers. Motivated by these considerations, in this paper we address the problem of determining the optimal geometric configuration of an acoustic sensor network at the ocean surface that will maximize the angle-related information available for underwater target positioning. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using the Cramer-Rao lower bound inequality, the trace of the inverse of the Fisher Information matrix (also called the Cramer-Rao Bound matrix) for the problem at hand is used to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration lends itself to an interesting geometrical interpretation and that the spreading of the sensor configuration depends explicitly on the intensity of the measurement noise and the target depth. Simulation examples illustrate the key results derived.

关键词： Robot sensing systems Sea measurements Noise measurement Noise Vectors Sea surface Acoustic measurements

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Closed-loop stability and performance optimization in LPV control based on a reduced parameter set

Closed-loop stability and performance optimization in LPV co...

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IEEE Conference on Decision and control

作者： C. Hoffmann S. M. Hashemi H. S. Abbas H. Werner Institute of Control Systems Hamburg University of Technology Hamburg Germany Mechatronics and Robotics Engineering Department Egypt-Japan University of Science and Technology Alexandria Egypt

ISBN: (纸本)9781467320658

A difficulty encountered in applying linear parameter-varying (LPV) control is the complexity of synthesis and implementation for large numbers of scheduling parameters. Often, heuristic solutions involve neglecting individual scheduling parameters, such that LPV controller synthesis methods become applicable. However, stability and performance guarantees are rendered void, if a controller design based on an approximate model is implemented on the original plant. In this paper, a posteriori conditions are proposed to assess closed-loop stability and performance and possibly recover guarantees. The controller - synthesized based on a reduced parameter set - is first transformed back to depend on the original parameters. Then analysis is performed with respect to the original plant model, which is considered to be accurate. Moreover, an iterative approach for optimizing controllers with few scheduling parameters is sketched. A two-degrees-of-freedom (2-DOF) robotic manipulator is considered as an illustrative example. Experimental results indicate a significant increase in performance.

关键词： Stability analysis Vectors Optimization Robots Linear matrix inequalities Scheduling Approximation methods

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Intermediate point norm optimal iterative learning control

Intermediate point norm optimal iterative learning control

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51st IEEE Conference on Decision and control, CDC 2012

作者： Owens, David H. Freeman, Chris T. Dinh, Thanh Van Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom School of Electronics and Computer Science University of Southampton Highfield SO17 1BJ United Kingdom Advanced Robotics Division Italian Institute of Technology Genoa Italy

A Norm-Optimal Iterative Learning control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties are presented, along with design guidelines and supporting experimental results using an electromechanical test facility. © 2012 IEEE.

关键词： Learning algorithms

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Herb 2.0: Lessons learned from developing a mobile manipulator for the home

Herb 2.0: Lessons learned from developing a mobile manipulat...

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作者： Srinivasa, Siddhartha S. Berenson, Dmitry Cakmak, Maya Collet, Alvaro Dogar, Mehmet R. Dragan, Anca D. Knepper, Ross A. Niemueller, Tim Strabala, Kyle Vande Weghe, Mike Ziegler, Julius Robotics Institute Carnegie Mellon University Pittsburgh PA 15213 United States Electrical Engineering and Computer Science Department University of California Berkeley Berkeley 94703 United States School of Interactive Computing Georgia Institute of Technology Atlanta GA 30332 United States Knowledge-based Systems Group RWTH Aachen University Aachen 52062 Germany Department of Measurement and Control Systems Karlsruhe Institute of Technology Karlsruhe D-76128 Germany

We present the hardware design, software architecture, and core algorithms of Herb 2.0, a bimanual mobile manipulator developed at the Personal robotics Lab at Carnegie Mellon University, Pittsburgh, PA. We have developed Herb 2.0 to perform useful tasks for and with people in human environments. We exploit two key paradigms in human environments: that they have structure that a robot can learn, adapt and exploit, and that they demand general-purpose capability in robotic systems. In this paper, we reveal some of the structure present in everyday environments that we have been able to harness for manipulation and interaction, comment on the particular challenges on working in human spaces, and describe some of the lessons we learned from extensively testing our integrated platform in kitchen and office environments. © 2012 IEEE.

关键词： Motion planning

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Navigation functions learning from experiments: Application to anthropomorphic grasping

Navigation functions learning from experiments: Application ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ioannis F. Filippidis Kostas J. Kyriakopoulos Panagiotis K. Artemiadis Control Systems Lab Department of Mechanical Engineering National and Technical University of Athens Zografou Greece ASU Human-Oriented Robotics and Control Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University USA

This paper proposes a method to construct Navigation Functions (NF) from experimental trajectories in an unknown environment. We want to approximate an unknown obstacle function and then use it within an NF. When navigating the same destinations with the experiments, this NF should produce the same trajectories as the experiments. This requirement is equivalent to a partial differential equation (PDE). Solving the PDE yields the unknown obstacle function, expressed with spline basis functions. We apply this new method to anthropomorphic grasping, producing automatic trajectories similar to the observed ones. The grasping experiments were performed for a set of different objects, Principal Component Analysis (PCA) allows reduction of the configuration space dimension, where the learning NF method is then applied.

关键词： Noise measurement Trajectory Splines (mathematics) Robots Grasping Principal component analysis Humans

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Lifelong education in robotics and mechatronics

Lifelong education in robotics and mechatronics

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Andreja Rojko Krzysztof Kozłowski Institute of Robotics / Department of Electrical Sustainable Energ FERI University of Maribor Maribor Slovenia Institute of Robotics / Department of Electrical Sustainable Energ FERI Delft University of Technology Delft Netherlands Chair of Control and Systems Engineering Poznan University of Technology Poznan Poland

Livelong education in electro-mechanical industry is increasingly important as it allows practicing engineers and technicians to gain the knowledge necessary to cope with the fast development and consequently with higher demands on their workplaces. This paper addresses different aspects of development and execution of such industrial training. Concrete solutions and results are presented including: (1) extensive international knowledge needs analysis in electro-mechanical sector, (2) e-learning solutions for industry including learning management systems and application of remote working stations/experiments for practical part of the training and (3) examples of the training modules from robotics developed for industry. Applied solutions and education methodology is evaluated by feedback obtained from the training participants. Based on a gained experience a long-term perspective and possible further development direction of modern industrial education is also addressed.

关键词： Training Service robots Educational institutions Mechatronics Companies

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Development of Prosthesis Grasp control systems on a Robotic Testbed

Development of Prosthesis Grasp Control Systems on a Robotic...

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IEEE RAS & EMBS International Conference on Biomedical robotics and Biomechatronics

作者： Bart Peerdeman Ugo Fabrizi Gianluca Palli Claudio Melchiorri Stefano Stramigioli Sarthak Misra MIRA - Institute for Biomedical Technology and Technical Medicine (Control Engineering Group) University of Twente LAR DEIS - Laboratory of Automation and Robotics Department of Electronics Computer Science and Systems University of Bologna

ISBN: (纸本)9781457711992

Modern myoelectric hand prostheses continue to increase in functionality, while their control is constrained by the limits of myoelectric input. This paper covers the development and testing of grasp control systems for multifunctional myoelectric prosthetic hands. The functionality of modern hand prostheses is often focused on the task of grasping, which can be divided into high-level grasp planning and low-level finger control. Initially, models can used to test these control systems, but for proper evaluation actual implementation on a physical system is required. The University of Bologna (UB) Hand IV prototype is an anthropomorphic, tendon-driven robotic hand, which makes it well-suited to represent the structure of modern prostheses. One of the main control systems tested in this paper is based on the intrinsically passive controller (IPC), the structure of which offers guaranteed passivity and stability. After several grasping tests, the systems are evaluated on compliant behavior, grasping ability, and dynamic appearance. IPC proves to be a powerful approach to interaction control, without the associated sensor requirements which could be difficult to meet in modern hand prostheses.

关键词： Grasp control systems Prosthetic hand Prosthesis robotic hand

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Online Learning Algorithm for Stackelberg Games in Problems with Hierarchy

Online Learning Algorithm for Stackelberg Games in Problems ...

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IEEE Annual Conference on Decision and control

作者： K. G. Vamvoudakis F. L. Lewis M. Johnson W. E. Dixon Center for Control Dynamical-systems and Computation (CCDC) University of California Automation and Robotics Research Institute University of Texas at Arlington NASA Ames Research Center Department of Mechanical and Aerospace Engineering University of Florida

ISBN: (纸本)9781467320658

This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. This adaptive optimal control method finds in real-time approximations of the optimal value and the Stackelberg-equilibrium solution, while also guaranteeing closed-loop stability. The optimal-adaptive algorithm is implemented as a separate actor/critic parametric network approximator structure for every player, and involves simultaneous continuous-time adaptation of the actor/critic networks. Novel tuning algorithms are given for the actor/critic networks. The convergence to the closed-loop Stackelberg equilibrium is proven and stability of the system is also guaranteed. A simulation example shows the effectiveness of the new online algorithm.

关键词： Stackelberg games Hierarchical control problems adaptive optimal control Social Hierarchy Game theory e-learning infinite horizon Best value algorithms

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Robust decentralized dynamic control for synchronization of a complex dynamical network with randomly occurring uncertainties

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Nonlinear Dynamics 2012年第1期70卷 559-570页

作者： Lee, Tae H. Park, Ju H. Wu, Zheng-Guang Lee, Sang-Choel Lee, Dong Ha Nonlinear Dynamics Group Department of Electrical Engineering Yeungnam University Kyongsan Republic of Korea National Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Yuquan Campus Hangzhou Zhejiang P.R. China Division of IT Convergence/Division of Robotics System DGIST Daegu Republic of Korea

This paper considers synchronization problem of an uncertain complex dynamical network. The norm-bounded uncertainties enter into the complex dynamical network in randomly ways, and such randomly occurring uncertainties (ROUs) obey certain mutually uncorrelated Bernoulli distributed white noise sequences. Under the circumstances, a robust $\mathcal{H}_{\infty}$ decentralized dynamic feedback controller is designed to achieve asymptotic synchronization of the network. Based on Lyapunov stability theory and linear matrix inequality (LMI) framework, the existence condition for feasible controllers is derived in terms of LMIs. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our result.

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